Hyunggi Chang is a Senior Field Application Engineer with eight years’ experience building production-ready Spatial AI and SLAM solutions for autonomous parking and augmented reality. He has designed lightweight, dependency-free visual-wheel odometry and semantic mapping systems that run single-threaded on embedded CPUs, and has applied SLAM to auto-labeling, self-calibration, and on-premise LLM/VLM tooling. His background spans industry and research—from developing cross-platform AR SDKs and object/ego-pose estimators to 3D hyperspectral reconstruction work at Cambridge—bringing both practical deployment chops and academic rigor. Based in Seoul and fluent in English and Korean, he documents his work on a technical blog and bridges low-level C++ engineering with higher-level AI tooling for real-world perception problems.
8 years of coding experience
8 years of employment as a software developer
Master of research Medical Robotics and Image-Guided Intervention, Master of research Medical Robotics and Image-Guided Intervention at Imperial College London
Bachelor’s Degree Manufacturing and Mechanical Engineering, Bachelor’s Degree Manufacturing and Mechanical Engineering at University of Warwick
C++ project template for developing computer vision applications
Contributions:1 release, 9 reviews, 96 commits in 9 months
computer-visioncpp
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